Applying Life Cycle Assessment in the climate effects of bioenergy systems

Transcription

1 Applying Life Cycle Assessment in the climate effects of bioenergy systems Dr Miguel Brandão and Prof AnneOe Cowie

2 Outline Life Cycle Assessment as a decision- support tool Policy Context Unresolved methodological issues in es@ma@ng climate effects of bioenergy systems with LCA iluc Modelling approaches & Alloca@on Prospects

3 Counter- intui*ve lessons from hard systems analysis What s beoer? Compos@ng vs Incinera@on Reusable nappies vs Disposable nappies Recycled bags vs Plas@c bags Recycled paper vs Virgin paper Organic food vs Conven@onal food Local food vs Imported food Bioenergy vs Fossil fuels

4 Food Miles

5 Greenhouse gas emissions from the food chain: 2004 in United Kingdom Source: SEI (2006) in defra (2007) 04/03/2015

6 EC policy needs European Commission response to the need for consistent and quality- assured life cycle data and assessments Integrated Product Policy (IPP), 2003: LCA is the best framework for assessing the environmental impacts of products, but the debate is ongoing about good Sustainable and Plan, 2008: To implement this policy, consistent and reliable data and methods are required to asses the overall environmental performance of products à European Platform on Life Cycle Assessment 04/03/2015

7 Necessity of Life Cycle Thinking in Policy and Business Avoid shicing of burdens: from one stage to another among countries across different environmental and health impacts and resources use from one to the next Fair basis for comparisons: same scope of assessments (stages, impacts, ) 04/03/2015

8 Life Cycle Assessment compared with process or site-specific environmental analysis ENVIRONMENT Raw materials and energy Extraction and processing of raw materials Manufacture Distribution and retailing Use, reuse and/or maintenance Waste management 04/03/2015 Product(s); solid waste; emissions to air, water and land Source: Hodgson et al. (1997) in Cowell (1998).

9 Aggregation to single score indicator Single indicator (overall environmental impact ) weigh@ng Human Health Natural environment Natural resources Area of Protec@on Environmental mechanism (impact pathway) Toxicity Radia@on Carcinogens Respiratory inorganics weigh@ng Summer smog Ozone layer Acidifica@on Eutrophica@on Ecotoxicity Climate change Land- use Resource deple@on Midpoints 04/03/2015 NOx, Cd, CO 2, CH 4, dioxins, energy, coal, silver ore, land use and other emissions and resource flows... Inventory

10 Policy Context: EU RED of 2009/28/EC on the of the use of energy from renewable sources 10% share of biofuels in transports by 2020 The addresses the produc*on and use of biofuel in a sustainable context (Ar@cle 17): Minimum GHG savings, rela@ve to fossil fuels of 35% (50% from 2017) Preserva@on of biodiversity on land used for biofuel produc@on Preserva@on of lands with high carbon stocks Requirement for good agricultural and environmental condi@ons ILUC effect refers to the GHG emissions from land- use conversions arising as a consequence of increased demand for land- based products

11 Crop displacement (Edwards et al. 2010)

12 Life cycle methodology RED s Annex V

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14 Typical and default values for biofuels Biofuel produc*on pathway Typical greenhouse gas emission saving Default greenhouse gas emission saving sugar beet ethanol 61 % 52 % wheat ethanol 32 % 16 % corn (maize) ethanol 56 % 49 % sugar cane ethanol 71 % 71 % rape seed biodiesel 45 % 38 % sunflower biodiesel 58 % 51 % soybean biodiesel 40 % 31 % palm oil biodiesel 36 % 19 % pure vegetable oil from rape seed 58 % 57 % European Commission Renewable Energies Direc@ve (2009) quan@fying the climate change effects of bioenergy

15 When the new ILUC proposal was launched on 17 October 2012, EU Climate Commissioner Connie Hedegaard said that some biofuels currently receiving EU subsidies were as bad as, or even worse than the fossil fuels that they replace. the climate change effects of bioenergy

16 New EU proposal (October 2012) to reduce iluc risk Amends both the Renewable Energy (2009/28/EC) and Fuel Quality (2009/30/EC) Avoids for the displacement of food crops for fuel A 60% GHG- saving for new biofuels installa@ons (from 1 July 2014) Including iluc factors in the repor@ng by suppliers and MS A 5% cap on the amount of biofuels in the EU s 2020 transport mix An end to public subsidies for 1 st genera@on biofuels acer 2020 unless they can demonstrate substan@al GHG savings Incen@ves for 2 nd and 3 rd genera@on biofuels A review of policy and scien@fic evidence on ILUC (in 2017)

17 indirect land- use change emissions from biofuels Cereals and other starch rich crops - 12 g CO 2 - eq/mj Sugars - 13 g CO 2 - eq/mj Oil crops - 55 g CO 2 - eq/mj Fossil fuel comparator g CO 2 - eq/mj (2008) 2012: 89.2 for diesel 2012: 90.7 for gasoline 2012: 90.3 for weighted average (3:1)

18 New factors for biofuels Palm Oil 105 g CO 2 - eq./mj Soybean 103 g CO 2 - eq./mj Rapeseed 95 g CO 2 - eq./mj Sunflower 86 g CO 2 - eq./mj Palm Oil with methane capture 83 g CO 2 - eq./mj Wheat (process fuel not specified) 64 g CO 2 - eq./mj Wheat (as process fuel natural gas used in CHP) 47 g CO 2 - eq./mj Corn (Maize) 43 g CO 2 - eq./mj Sugar Cane 36 g CO 2 - eq./mj Sugar Beet 34 g CO 2 - eq./mj Wheat (straw as process fuel in CHP plants) 35 g CO 2 - eq./mj 2G Ethanol (land- using) 32 g CO 2 - eq./mj 2G Biodiesel (land- using) 21 g CO 2 - eq./mj 2G Ethanol (non- land using) 9 g CO 2 - eq./mj 2G Biodiesel (non- land using) 9 g CO 2 - eq./mj No GHG saving! <35% GHG saving 35-50% GHG saving 50-60% GHG saving >60%

19 issues in iluc modelling 1. GHG emissions from LUC Land requirements Reference system 2. Ascribing LUC to their drivers 3. Dealing with modelling vs. expansion vs. displacement Treatment of by- products

20 Where does increased supply come from? agricultural land 1. Displacement decreased food availability or iluc 2. Yield increases increased input use Newly- converted agricultural land 3. Direct Land Use Change Increased carbon emissions

21 modelling approaches Economic- equilibrium models Biophysical models Price Usually no constraints considered, full price Black boxes Transparent physical 04/03/2015 IEA Bioenergy Task 38 Webinar - The Applica@on of Life Cycle Assessment in quan@fying the climate change effects of bioenergy

22 Legisla*ve milestones 2008: EP asked EC to look into iluc 2010: importance of iluc recognised but doubts about appropriate methodology October 2012: proposal for considering iluc with factors for different crop groups and a 5% cap June 2014: EU Council reaches agreement: No subsidies for worst offenders post % cap from 1 st genera@on biofuels 0.5% target for advanced biofuels February 2015: Approved by EP Environment CommiOee (374 proposed amendments on iluc!) 6% cap Boost advanced biofuels (1.25%) Reduce iluc (EU biofuels policy budget of 10 billion / year)

23 Comparison of iluc models Schmidt J H and Brandão M (2013), LCA screening of biofuels iluc, biomass manipulation and soil carbon. Concito, Copenhagen 23

24 iluc factors from different models Source iluc Factor (g CO 2 - eq./mj) Searchinger et al., Audsley et al., t CO 2 - eq./ha of agricultural land used Cederberg et al., 2011 n/a EPA RFS Dumor@er et al., Tyner et al., JRC 36 JRC ethanol 4 to 20 JRC biodiesel 36 to 60

25 Are models suitable for determining ILUC factors? Source: Berndes, G., Bird, N. & Cowie, A., Bioenergy, land use change and climate change Background Technical Report, Paris: Energy Agency (IEA).

26 Large variability in published GHG emissions Life Cycle Greenhouse Gas Emissions (g CO2e / kwh) Source: Heath et al. (2010) Special Session on Meta-Analysis of Energy LCAs. InLCA X Dedicated Feedstocks Biopower (no LUC) Residues With Avoided Emission Credits Photovoltaics Technologies powered by renewable resources Concentrating Solar Power Geothermal Hydropower Ocean Energy Wind Nuclear Natural Gas Oil Coal Technologies powered by non-renewable resources Count of Estimates Count of References quan@fying the climate change effects of bioenergy

27 and modelling UNEP/SETAC (2011). Shonan LCA database guidance principles: AXribu*onal approach: System modelling approach in which inputs and outputs are axributed to the unit of a product system by linking and/or par@@oning the unit processes of the system according to a norma*ve rule. Consequen*al approach: System modelling approach in which ac@vi@es in a product system are linked so that ac*vi*es are included in the product system to the extent that they are expected to change as a consequence of a change in demand for the func@onal unit.

28 and modelling (Weidema, 2003) AXribu*onal Consequen*al

29 System boundary - Dairy cow example 04/03/2015 IEA Bioenergy Task Webinar - The Applica@on of Life Cycle Assessment in

30 System boundary for

31 System boundary for and ISO/CLCA (substitution)

32 impossible are created Milk Meat Milk Meat

33 Unallocated milking cow (per 100kg DM feed) 100kg DM feed Σoutputs = 100kg 2.0kg CH kg Manure 28.3kg C in CO kg respiratory water 9.3kg Milk 2.2kg Meat Milk: 77% of economic turnover Meat: 23% of economic turnover

34 Meat and Milk from the output system Dairy cow Original systems System expansion Dry maxer alloca*on Economic alloca*on Dairy cow Meat caxle Milk = Dairy Cow - Meat caxle Meat = Meat caxle Milk 81% Meat 19% Milk 77% Meat 23% Feed DM Milk DM Meat DM CH Manure DM C in CO Respiratory water Mass balance: Feed C Milk C Meat C CH4- C Manure C C in CO C balance: quan@fying the climate change effects of bioenergy

35 Allocated milking cow (economic milk 77%) 77kg DM feed Σoutputs = 77.5kg 1.5kg CH kg Manure 21.8kg C in CO kg respiratory water 9.3kg Milk 2.2 Meat Milk: 77% of economic turnover Meat: 23% of economic turnover 35

36 The co- product algorithm Case study: Small demand for protein feed Soybean 2.77 kg soybean Palm oil mill kg FFB Oil palm produc@on kg Land Use Market for generic vegetable oil Barley produc@on kg veg. oil kg barley Soybean mill Barley to generic feed market 0.53 kg veg. oil 2.13 kg meal MJ kg crude protein Soybean meal to generic feed market 1 kg 20.5 MJ energy feed Market for protein feed, crude 1 kg

37 To compare: An system Case study: Small demand for protein feed Land Use Rape Oil palm Soybean Sunflower Wheat Barley Rape oil meal mill Sunflower oil meal mill Wheat flour mill bran & germ Corn protein Palm oil meal mill Soybean meal to generic feed market Barley to generic feed protein market Market for protein feed, crude

38 Results for 1 kg soybean meal [kg CO 2 - equivalents] Activity: Consequential Attributional Total of all activities iluc Soybean cultivation Natural gas Light fuel oil Electricity BR Other chemicals Lorry Farm capital equipment Farm services Oil mill Diesel Oil palm cultivation <0.001 Barley cultivation <0.001 Fertiliser Other activities

39 Precision vs. Accuracy High Precision Low Accuracy Biased results High Accuracy Low Precision Representative Results Brandão et al. (2014) The Use of Life Cycle Assessment in the Support of Robust (Climate) Policy Making. Journal of Industrial Ecology

40 It is much more important to be able to survey the set of possible systems approximately than to examine the wrong system exactly. It is beher to be approximately right than precisely wrong. Tribus and El- Sayed (1982)

41 Conclusions and Outlook LCAs relevance for policy support growing Several developments and ongoing BeOer methods, databases, socware Lack of consensus Increasing needed in LCA LCA of bioenergy systems Methodological choices in LCA determine results Biomass/biofuels not necessarily beoer Indirect effects important All models are wrong, some are useful Non- shicing of burdens

42 Thank you!